---
language:
- mr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-mr
  results:
  - task: 
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      type: mozilla-foundation/common_voice_8_0
      name: Common Voice 8
      args: mr
    metrics:
      - type: wer    # Required. Example: wer
        value: 31.57  # Required. Example: 20.90
        name: Test WER    # Optional. Example: Test WER
      - name: Test CER
        type: cer
        value: 6.93
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.494580
- Wer: 0.395909

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 200.0
- mixed_precision_training: Native AMP

### Training results

/ Step / Training Loss / Validation Loss / Wer /
|---|---|---|---|
/ 400 / 3.794000 / 3.532227 / 1.000000 / 
/ 800 / 3.362400 / 3.359044 / 1.000000 / 
/ 1200 / 2.293900 / 1.011279 / 0.829924 / 
/ 1600 / 1.233000 / 0.502743 / 0.593662 / 
/ 2000 / 0.962600 / 0.412519 / 0.496992 / 
/ 2400 / 0.831800 / 0.402903 / 0.493783 / 
/ 2800 / 0.737000 / 0.389773 / 0.469314 / 
/ 3200 / 0.677100 / 0.373987 / 0.436021 / 
/ 3600 / 0.634400 / 0.383823 / 0.432010 / 
/ 4000 / 0.586000 / 0.375610 / 0.419575 / 
/ 4400 / 0.561000 / 0.387891 / 0.418371 / 
/ 4800 / 0.518500 / 0.386357 / 0.417569 / 
/ 5200 / 0.515300 / 0.415069 / 0.430004 / 
/ 5600 / 0.478100 / 0.399211 / 0.408744 / 
/ 6000 / 0.468100 / 0.424542 / 0.402327 / 
/ 6400 / 0.439400 / 0.430979 / 0.410750 / 
/ 6800 / 0.429600 / 0.427700 / 0.409146 / 
/ 7200 / 0.400300 / 0.451111 / 0.419976 / 
/ 7600 / 0.395100 / 0.463446 / 0.405134 / 
/ 8000 / 0.381800 / 0.454752 / 0.407942 / 
/ 8400 / 0.371500 / 0.461547 / 0.404733 / 
/ 8800 / 0.362500 / 0.461543 / 0.411151 / 
/ 9200 / 0.338200 / 0.468299 / 0.417168 / 
/ 9600 / 0.338800 / 0.480989 / 0.412355 / 
/ 10000 / 0.317600 / 0.475700 / 0.410750 / 
/ 10400 / 0.315100 / 0.478920 / 0.403530 / 
/ 10800 / 0.296200 / 0.480600 / 0.398315 / 
/ 11200 / 0.299000 / 0.477083 / 0.393502 / 
/ 11600 / 0.290000 / 0.465646 / 0.393903 / 
/ 12000 / 0.290900 / 0.490041 / 0.405937 / 
/ 12400 / 0.275600 / 0.489354 / 0.399519 / 
/ 12800 / 0.272600 / 0.494580 / 0.395909 /


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.3.dev0
- Tokenizers 0.11.0


### Eval results on Common Voice 8 "test" (WER):

| Without LM | With LM |
|---|---|
| 40.513437625350984 | 31.56839149618933 |